Efficacy and Safety of Allogeneic Hematopoietic Stem Cell Transplantation in Curing Sickle Cell Disease: A Systematic Review and Meta-Analysis of Single-Arm Studies
Bibliographic record
Abstract
Sickle cell disease (SCD) is a life-threatening hemolytic genetic disorder affecting approximately 20 to 25 million people globally. Conventional treatment, like hydroxyurea, is supportive but not a cure. Allogeneic hematopoietic stem cell transplantation (Allo-HSCT) has gained popularity recently as it offers a potential cure for SCD. Although several independent studies exist supporting this, there is a lack of consolidated evidence for a more comprehensive analysis of clinical outcomes. In this systematic review and meta-analysis, we assessed the safety and efficacy of allo-HSCT in SCD, offering information on results for various age groups, donor types, conditioning procedures/regimens, and stem cell sources. A systematic literature search was carried out in PubMed and Scopus for articles published between January 2010 and March 2025. Articles that satisfied the inclusion requirements were subjected to quality assessment using the Newcastle-Ottawa Scale (NOS). Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines were followed throughout. Statistical analyses were performed using meta, an R package. The meta-analysis of 58 studies (n = 7931) revealed allo-HSCT to have 94%, 86%, 20%, 14%, 9%, and 6% for overall survival (OS), event-free survival (EFS), acute graft-versus-host disease (aGVHD), chronic graft-versus-host disease (cGVHD), graft-failure (GF), and mortality, respectively, in SCD. Subgroup analysis demonstrated that clinical outcomes varied based on the type of donors, conditioning procedures/regimens and stem cell sources. The findings of this study show that allo-HSCT is safe and efficacious in curing SCD. GF and GVHD issues could be reduced by following personalized conditioning regimens/post-transplantation prophylaxis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".